1. Social Graph Symposium Panel
Ho John Lee | Principal Program Manager | Bing Social Search
2. About me:
Ho John Lee
hojohn.lee@microsoft.com
twitter.com/hjl
Past: Bing Twitter (v1), SocialQuant, trading, investing/consulting (China, India)
HP Labs, MIT, Stanford, Harvard
Current: Bing Social Search – graph and time series analysis, data mining
Twitter, Facebook, new products, technical planning
3. What can we do by observing social networks?
On the internet, no one knows you’re a dog.
But in social networks, we can tell if you act like a dog, what groups you belong to, and some of your interests
4. How many Twitter users are there?
from a search on twopular, May 2009
5. Graph analysis for relevance and ranking
Spam marketing campaign
(teeth whitening)
Naturally connected community (#smx)
Real time relevance needs data mining to filter and rank based on history
Spammy communities can be highly visible
Social graph, topic/concept graph, and behavior/gesture graphs are all useful tools
6. Information diffusion in the graph
Observed incidence network of retweets in Twitter
Kwak, Lee, et al, What is Twitter, a Social Network or a News Media? WWW2010
Information flow and behaviors form an implicit interaction graph
7. Topic / sentiment range, volume, trend analysis
What is the baseline rate of mentions / sentiment per unit time?
Look for changes in attention flow around a subject, location, topic
Watch for correlated signals from multiple sources
Consider source relevance and authority as well
8. Applying graph analysis
Attention flow vs information flow
Leads to utility functions, cost functions
Variable diffusion rates by actor / network / info type
Predicting interests and affiliations
Content creation follows attention
Self-organized communities of attention
If there’s no content, you can ask for some
Observable propagation of information
9. Clustering and fuzzing properties and identities
* Frequently used terms can identify interests, affinities, latent query intent
* But can potentially be used to identify likely individual users!
* Infochaff – fuzzing out identity, behavior, properties
10. Thank You
Ho John Lee
hojohn.lee@microsoft.com
twitter.com/hjl

1. Social Graph Symposium Panel
Ho John Lee | Principal Program Manager | Bing Social Search
2. About me:
Ho John Lee
hojohn.lee@microsoft.com
twitter.com/hjl
Past: Bing Twitter (v1), SocialQuant, trading, investing/consulting (China, India)
HP Labs, MIT, Stanford, Harvard
Current: Bing Social Search – graph and time series analysis, data mining
Twitter, Facebook, new products, technical planning
3. What can we do by observing social networks?
On the internet, no one knows you’re a dog.
But in social networks, we can tell if you act like a dog, what groups you belong to, and some of your interests
4. How many Twitter users are there?
from a search on twopular, May 2009
5. Graph analysis for relevance and ranking
Spam marketing campaign
(teeth whitening)
Naturally connected community (#smx)
Real time relevance needs data mining to filter and rank based on history
Spammy communities can be highly visible
Social graph, topic/concept graph, and behavior/gesture graphs are all useful tools
6. Information diffusion in the graph
Observed incidence network of retweets in Twitter
Kwak, Lee, et al, What is Twitter, a Social Network or a News Media? WWW2010
Information flow and behaviors form an implicit interaction graph
7. Topic / sentiment range, volume, trend analysis
What is the baseline rate of mentions / sentiment per unit time?
Look for changes in attention flow around a subject, location, topic
Watch for correlated signals from multiple sources
Consider source relevance and authority as well
8. Applying graph analysis
Attention flow vs information flow
Leads to utility functions, cost functions
Variable diffusion rates by actor / network / info type
Predicting interests and affiliations
Content creation follows attention
Self-organized communities of attention
If there’s no content, you can ask for some
Observable propagation of information
9. Clustering and fuzzing properties and identities
* Frequently used terms can identify interests, affinities, latent query intent
* But can potentially be used to identify likely individual users!
* Infochaff – fuzzing out identity, behavior, properties
10. Thank You
Ho John Lee
hojohn.lee@microsoft.com
twitter.com/hjl

1. Social Graph Symposium Panel
Ho John Lee | Principal Program Manager | Bing Social Search
2. About me:
Ho John Lee
hojohn.lee@microsoft.com
twitter.com/hjl
Past: Bing Twitter (v1), SocialQuant, trading, investing/consulting (China, India)
HP Labs, MIT, Stanford, Harvard
Current: Bing Social Search – graph and time series analysis, data mining
Twitter, Facebook, new products, technical planning
3. What can we do by observing social networks?
On the internet, no one knows you’re a dog.
But in social networks, we can tell if you act like a dog, what groups you belong to, and some of your interests
4. How many Twitter users are there?
from a search on twopular, May 2009
5. Graph analysis for relevance and ranking
Spam marketing campaign
(teeth whitening)
Naturally connected community (#smx)
Real time relevance needs data mining to filter and rank based on history
Spammy communities can be highly visible
Social graph, topic/concept graph, and behavior/gesture graphs are all useful tools
6. Information diffusion in the graph
Observed incidence network of retweets in Twitter
Kwak, Lee, et al, What is Twitter, a Social Network or a News Media? WWW2010
Information flow and behaviors form an implicit interaction graph
7. Topic / sentiment range, volume, trend analysis
What is the baseline rate of mentions / sentiment per unit time?
Look for changes in attention flow around a subject, location, topic
Watch for correlated signals from multiple sources
Consider source relevance and authority as well
8. Applying graph analysis
Attention flow vs information flow
Leads to utility functions, cost functions
Variable diffusion rates by actor / network / info type
Predicting interests and affiliations
Content creation follows attention
Self-organized communities of attention
If there’s no content, you can ask for some
Observable propagation of information
9. Clustering and fuzzing properties and identities
* Frequently used terms can identify interests, affinities, latent query intent
* But can potentially be used to identify likely individual users!
* Infochaff – fuzzing out identity, behavior, properties
10. Thank You
Ho John Lee
hojohn.lee@microsoft.com
twitter.com/hjl

1. Social Graph Symposium Panel
Ho John Lee | Principal Program Manager | Bing Social Search
2. About me:
Ho John Lee
hojohn.lee@microsoft.com
twitter.com/hjl
Past: Bing Twitter (v1), SocialQuant, trading, investing/consulting (China, India)
HP Labs, MIT, Stanford, Harvard
Current: Bing Social Search – graph and time series analysis, data mining
Twitter, Facebook, new products, technical planning
3. What can we do by observing social networks?
On the internet, no one knows you’re a dog.
But in social networks, we can tell if you act like a dog, what groups you belong to, and some of your interests
4. How many Twitter users are there?
from a search on twopular, May 2009
5. Graph analysis for relevance and ranking
Spam marketing campaign
(teeth whitening)
Naturally connected community (#smx)
Real time relevance needs data mining to filter and rank based on history
Spammy communities can be highly visible
Social graph, topic/concept graph, and behavior/gesture graphs are all useful tools
6. Information diffusion in the graph
Observed incidence network of retweets in Twitter
Kwak, Lee, et al, What is Twitter, a Social Network or a News Media? WWW2010
Information flow and behaviors form an implicit interaction graph
7. Topic / sentiment range, volume, trend analysis
What is the baseline rate of mentions / sentiment per unit time?
Look for changes in attention flow around a subject, location, topic
Watch for correlated signals from multiple sources
Consider source relevance and authority as well
8. Applying graph analysis
Attention flow vs information flow
Leads to utility functions, cost functions
Variable diffusion rates by actor / network / info type
Predicting interests and affiliations
Content creation follows attention
Self-organized communities of attention
If there’s no content, you can ask for some
Observable propagation of information
9. Clustering and fuzzing properties and identities
* Frequently used terms can identify interests, affinities, latent query intent
* But can potentially be used to identify likely individual users!
* Infochaff – fuzzing out identity, behavior, properties
10. Thank You
Ho John Lee
hojohn.lee@microsoft.com
twitter.com/hjl
RESEARCH: Insights from the latest social graph studies

Moderator: Eric Siegel – President at Prediction Impact and Conference Chair at Predictive Analytics World

1. Social Graph Symposium Panel
Ho John Lee | Principal Program Manager | Bing Social Search
2. About me:
Ho John Lee
hojohn.lee@microsoft.com
twitter.com/hjl
Past: Bing Twitter (v1), SocialQuant, trading, investing/consulting (China, India)
HP Labs, MIT, Stanford, Harvard
Current: Bing Social Search – graph and time series analysis, data mining
Twitter, Facebook, new products, technical planning
3. What can we do by observing social networks?
On the internet, no one knows you’re a dog.
But in social networks, we can tell if you act like a dog, what groups you belong to, and some of your interests
4. How many Twitter users are there?
from a search on twopular, May 2009
5. Graph analysis for relevance and ranking
Spam marketing campaign
(teeth whitening)
Naturally connected community (#smx)
Real time relevance needs data mining to filter and rank based on history
Spammy communities can be highly visible
Social graph, topic/concept graph, and behavior/gesture graphs are all useful tools
6. Information diffusion in the graph
Observed incidence network of retweets in Twitter
Kwak, Lee, et al, What is Twitter, a Social Network or a News Media? WWW2010
Information flow and behaviors form an implicit interaction graph
7. Topic / sentiment range, volume, trend analysis
What is the baseline rate of mentions / sentiment per unit time?
Look for changes in attention flow around a subject, location, topic
Watch for correlated signals from multiple sources
Consider source relevance and authority as well
8. Applying graph analysis
Attention flow vs information flow
Leads to utility functions, cost functions
Variable diffusion rates by actor / network / info type
Predicting interests and affiliations
Content creation follows attention
Self-organized communities of attention
If there’s no content, you can ask for some
Observable propagation of information
9. Clustering and fuzzing properties and identities
* Frequently used terms can identify interests, affinities, latent query intent
* But can potentially be used to identify likely individual users!
* Infochaff – fuzzing out identity, behavior, properties
10. Thank You
Ho John Lee
hojohn.lee@microsoft.com
twitter.com/hjl

1. Social Graph Symposium Panel
Ho John Lee | Principal Program Manager | Bing Social Search
2. About me:
Ho John Lee
hojohn.lee@microsoft.com
twitter.com/hjl
Past: Bing Twitter (v1), SocialQuant, trading, investing/consulting (China, India)
HP Labs, MIT, Stanford, Harvard
Current: Bing Social Search – graph and time series analysis, data mining
Twitter, Facebook, new products, technical planning
3. What can we do by observing social networks?
On the internet, no one knows you’re a dog.
But in social networks, we can tell if you act like a dog, what groups you belong to, and some of your interests
4. How many Twitter users are there?
from a search on twopular, May 2009
5. Graph analysis for relevance and ranking
Spam marketing campaign
(teeth whitening)
Naturally connected community (#smx)
Real time relevance needs data mining to filter and rank based on history
Spammy communities can be highly visible
Social graph, topic/concept graph, and behavior/gesture graphs are all useful tools
6. Information diffusion in the graph
Observed incidence network of retweets in Twitter
Kwak, Lee, et al, What is Twitter, a Social Network or a News Media? WWW2010
Information flow and behaviors form an implicit interaction graph
7. Topic / sentiment range, volume, trend analysis
What is the baseline rate of mentions / sentiment per unit time?
Look for changes in attention flow around a subject, location, topic
Watch for correlated signals from multiple sources
Consider source relevance and authority as well
8. Applying graph analysis
Attention flow vs information flow
Leads to utility functions, cost functions
Variable diffusion rates by actor / network / info type
Predicting interests and affiliations
Content creation follows attention
Self-organized communities of attention
If there’s no content, you can ask for some
Observable propagation of information
9. Clustering and fuzzing properties and identities
* Frequently used terms can identify interests, affinities, latent query intent
* But can potentially be used to identify likely individual users!
* Infochaff – fuzzing out identity, behavior, properties
10. Thank You
Ho John Lee
hojohn.lee@microsoft.com
twitter.com/hjl

Lately I’ve been looking forward to watching the daily Rocketboom video blog, and have struggled to explain both Rocketboom and video blogging in general to non-blog-reading, TV-watching folks, i.e. most normal people. So until I get around to writing a longer introduction to video (and regular) blogging for my non-blogging / non-blog-reading friends, just go check it out .

I enjoyed this clip posted earlier this week, which features David Letterman-style page tossing at the end of each article, David Lynch’s (of Eraserhead, Twin Peaks, Blue Velvet etc) daily weather report from L.A., and a vintage black-and-white television ad for Wham-O frisbees.

Rocketboom looks like it’s sort of a group project at Parsons School of Design in New York, produced by Andrew Baron, who teaches there, so it’s not exactly one person, a camcorder, and a home computer on the internet. But it has relatively good production value and is quite entertaining, for very little investment on their part.

Lately I’ve been looking forward to watching the daily Rocketboom video blog, and have struggled to explain both Rocketboom and video blogging in general to non-blog-reading, TV-watching folks, i.e. most normal people. So until I get around to writing a longer introduction to video (and regular) blogging for my non-blogging / non-blog-reading friends, just go check it out .

I enjoyed this clip posted earlier this week, which features David Letterman-style page tossing at the end of each article, David Lynch’s (of Eraserhead, Twin Peaks, Blue Velvet etc) daily weather report from L.A., and a vintage black-and-white television ad for Wham-O frisbees.

Rocketboom looks like it’s sort of a group project at Parsons School of Design in New York, produced by Andrew Baron, who teaches there, so it’s not exactly one person, a camcorder, and a home computer on the internet. But it has relatively good production value and is quite entertaining, for very little investment on their part.

Lately I’ve been looking forward to watching the daily Rocketboom video blog, and have struggled to explain both Rocketboom and video blogging in general to non-blog-reading, TV-watching folks, i.e. most normal people. So until I get around to writing a longer introduction to video (and regular) blogging for my non-blogging / non-blog-reading friends, just go check it out .

I enjoyed this clip posted earlier this week, which features David Letterman-style page tossing at the end of each article, David Lynch’s (of Eraserhead, Twin Peaks, Blue Velvet etc) daily weather report from L.A., and a vintage black-and-white television ad for Wham-O frisbees.

Rocketboom looks like it’s sort of a group project at Parsons School of Design in New York, produced by Andrew Baron, who teaches there, so it’s not exactly one person, a camcorder, and a home computer on the internet. But it has relatively good production value and is quite entertaining, for very little investment on their part.

Lately I’ve been looking forward to watching the daily Rocketboom video blog, and have struggled to explain both Rocketboom and video blogging in general to non-blog-reading, TV-watching folks, i.e. most normal people. So until I get around to writing a longer introduction to video (and regular) blogging for my non-blogging / non-blog-reading friends, just go check it out .

I enjoyed this clip posted earlier this week, which features David Letterman-style page tossing at the end of each article, David Lynch’s (of Eraserhead, Twin Peaks, Blue Velvet etc) daily weather report from L.A., and a vintage black-and-white television ad for Wham-O frisbees.

Rocketboom looks like it’s sort of a group project at Parsons School of Design in New York, produced by Andrew Baron, who teaches there, so it’s not exactly one person, a camcorder, and a home computer on the internet. But it has relatively good production value and is quite entertaining, for very little investment on their part.

Lately I’ve been looking forward to watching the daily Rocketboom video blog, and have struggled to explain both Rocketboom and video blogging in general to non-blog-reading, TV-watching folks, i.e. most normal people. So until I get around to writing a longer introduction to video (and regular) blogging for my non-blogging / non-blog-reading friends, just go check it out .

I enjoyed this clip posted earlier this week, which features David Letterman-style page tossing at the end of each article, David Lynch’s (of Eraserhead, Twin Peaks, Blue Velvet etc) daily weather report from L.A., and a vintage black-and-white television ad for Wham-O frisbees.

Rocketboom looks like it’s sort of a group project at Parsons School of Design in New York, produced by Andrew Baron, who teaches there, so it’s not exactly one person, a camcorder, and a home computer on the internet. But it has relatively good production value and is quite entertaining, for very little investment on their part.

Lately I’ve been looking forward to watching the daily Rocketboom video blog, and have struggled to explain both Rocketboom and video blogging in general to non-blog-reading, TV-watching folks, i.e. most normal people. So until I get around to writing a longer introduction to video (and regular) blogging for my non-blogging / non-blog-reading friends, just go check it out .

I enjoyed this clip posted earlier this week, which features David Letterman-style page tossing at the end of each article, David Lynch’s (of Eraserhead, Twin Peaks, Blue Velvet etc) daily weather report from L.A., and a vintage black-and-white television ad for Wham-O frisbees.

Rocketboom looks like it’s sort of a group project at Parsons School of Design in New York, produced by Andrew Baron, who teaches there, so it’s not exactly one person, a camcorder, and a home computer on the internet. But it has relatively good production value and is quite entertaining, for very little investment on their part.

Lately I’ve been looking forward to watching the daily Rocketboom video blog, and have struggled to explain both Rocketboom and video blogging in general to non-blog-reading, TV-watching folks, i.e. most normal people. So until I get around to writing a longer introduction to video (and regular) blogging for my non-blogging / non-blog-reading friends, just go check it out .

I enjoyed this clip posted earlier this week, which features David Letterman-style page tossing at the end of each article, David Lynch’s (of Eraserhead, Twin Peaks, Blue Velvet etc) daily weather report from L.A., and a vintage black-and-white television ad for Wham-O frisbees.

Rocketboom looks like it’s sort of a group project at Parsons School of Design in New York, produced by Andrew Baron, who teaches there, so it’s not exactly one person, a camcorder, and a home computer on the internet. But it has relatively good production value and is quite entertaining, for very little investment on their part.

Lately I’ve been looking forward to watching the daily Rocketboom video blog, and have struggled to explain both Rocketboom and video blogging in general to non-blog-reading, TV-watching folks, i.e. most normal people. So until I get around to writing a longer introduction to video (and regular) blogging for my non-blogging / non-blog-reading friends, just go check it out .

I enjoyed this clip posted earlier this week, which features David Letterman-style page tossing at the end of each article, David Lynch’s (of Eraserhead, Twin Peaks, Blue Velvet etc) daily weather report from L.A., and a vintage black-and-white television ad for Wham-O frisbees.

Rocketboom looks like it’s sort of a group project at Parsons School of Design in New York, produced by Andrew Baron, who teaches there, so it’s not exactly one person, a camcorder, and a home computer on the internet. But it has relatively good production value and is quite entertaining, for very little investment on their part.

Lately I’ve been looking forward to watching the daily Rocketboom video blog, and have struggled to explain both Rocketboom and video blogging in general to non-blog-reading, TV-watching folks, i.e. most normal people. So until I get around to writing a longer introduction to video (and regular) blogging for my non-blogging / non-blog-reading friends, just go check it out .

I enjoyed this clip posted earlier this week, which features David Letterman-style page tossing at the end of each article, David Lynch’s (of Eraserhead, Twin Peaks, Blue Velvet etc) daily weather report from L.A., and a vintage black-and-white television ad for Wham-O frisbees.

Rocketboom looks like it’s sort of a group project at Parsons School of Design in New York, produced by Andrew Baron, who teaches there, so it’s not exactly one person, a camcorder, and a home computer on the internet. But it has relatively good production value and is quite entertaining, for very little investment on their part.

Home | Institute for the Study of War – The Institute for the Study of War (ISW) is a non-partisan, non-profit, public policy research organization. ISW advances an informed understanding of military affairs through reliable research, trusted analysis, and innovative education.

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Chip and PIN is Broken – Steven J. Murdoch, Saar Drimer, Ross Anderson, Mike Bond – 2010 IEEE Symposium on Security and Privacy – In this paper we describe and demonstrate a
protocol flaw which allows criminals to use a genuine card
to make a payment without knowing the card’s PIN, and
to remain undetected even when the merchant has an online
connection to the banking network. The fraudster performs a
man-in-the-middle attack to trick the terminal into believing
the PIN verified correctly, while telling the issuing bank that
no PIN was entered at all. The paper considers how the
flaws arose, why they remained unknown despite EMV’s wide
deployment for the best part of a decade, and how they might
be fixed. Because we have found and validated a practical
attack against the core functionality of EMV, we conclude
that the protocol is broken.

Chip and PIN is Broken – Steven J. Murdoch, Saar Drimer, Ross Anderson, Mike Bond – 2010 IEEE Symposium on Security and Privacy – In this paper we describe and demonstrate a
protocol flaw which allows criminals to use a genuine card
to make a payment without knowing the card’s PIN, and
to remain undetected even when the merchant has an online
connection to the banking network. The fraudster performs a
man-in-the-middle attack to trick the terminal into believing
the PIN verified correctly, while telling the issuing bank that
no PIN was entered at all. The paper considers how the
flaws arose, why they remained unknown despite EMV’s wide
deployment for the best part of a decade, and how they might
be fixed. Because we have found and validated a practical
attack against the core functionality of EMV, we conclude
that the protocol is broken.